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The Who's Who of AI

What credible people across AI noticed, why it matters, and where the field is converging or disagreeing.

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Showing developments with attributable Opportunity & adoption reactions.

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Building & implementation Opportunity & adoption
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Reaction converging Verbalizable Representations Form a Global Workspace in Language Models Opportunity & adoption · 5 attributable reactions
Showing signals surfaced by Nafnlaus 🇮🇸 🇺🇦 ×
New & accelerating

What is moving across the network now

One card per development. Sources are clustered; reaction bundles describe these posts, never the people behind them.

Developing Models & releases Research 2d ago
⚡ 3 h early
global workspace theory language models paper

Verbalizable Representations Form a Global Workspace in Language Models

6 experts across 4 network communities independently surfaced this.

Why this matches Opportunity & adoption reaction 4 attributable expert contributions · Mark Riedl, Matthew Kirschenbaum, Nafnlaus 🇮🇸 🇺🇦
“here is the Anthropic blog: transformer-circuits.pub/2026/workspa... I don't really like the framing of whether LLMs are conscious or not. It's completely unnecessary. As is the hand-waiving about whether LLMs have something equivalent to the (functional) g…” evidence ↗
6 experts 4 communities 1 sources clustered
Mark Riedl Tim Kellogg Matthew Kirschenbaum Edouard Machery Nafnlaus 🇮🇸 🇺🇦 david-p-reichert.bsky.social
How the network is reacting 4 experts are independently emphasizing opportunity & adoption.
Reaction converging

Opportunity & adoption

4 experts

New capabilities, benefits and practical upside.

“here is the Anthropic blog: transformer-circuits.pub/2026/workspa... I don't really like the framing of whether LLMs are conscious or not. It's completely unnecessary. As is the hand-waiving about whether LLMs have something equivalent to the (functional) g…”

Building & implementation

1 expert

How teams are shipping and applying it.

“Anthropic uses the word “conscious” 206 times in their latest research Specifically, they’re showing that LLMs implement one of the leading explanations of consciousness in humans (see pic) transformer-circuits.pub/2026/workspa...”

7 experts discussed this · 203 posts
Anil Dash: this is not an accurate description of what's happening. not least because I can write code and get them to output something different there. I can understand why it *seems* that way, but this is j…
Anil Dash: Who are you explaining this to?
Anil Dash: Do you see why explaining "All output from AI has to be validated" in a reply to me here is... not a useful contribution?
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Primary source transformer-circuits.pub ↗
Debates gaining attention

What experts are discussing without an anchoring article

4 experts · 34 posts · 4d ago
Gus Ravyn Nafnlaus 🇮🇸 🇺🇦 austegard.com
Matches Opportunity & adoption
“The problem with longer draft is that you stop with any speed up if the small model needs to generate too many tokens And thanks for the feedback. The diffusion Gemma team will be happy!” evidence ↗
Multiple readings Concern & critique · 1 Opportunity & adoption · 1 Questions & unknowns · 1
Gus: What would you like to see on Gemma 5?
Gus: Thanks Ana! Took note of everything.
Open the thread →
4 experts · 21 posts · 1d ago
Eugene Vinitsky Adam Wiemerslage Sam Barrett, PhD Nafnlaus 🇮🇸 🇺🇦
Matches Opportunity & adoption
“Removing voice is time-consuming for no benefit, and people vary greatly in how good they are in detecting it. Also, AI voice rubs off on frequent users, thus leading to actual human speech taking …” evidence ↗
Multiple readings Concern & critique · 1 Research & technical analysis · 1 Opportunity & adoption · 1
Eugene Vinitsky: It takes so long to write a paper because we are crazy about not making mistakes and checking as many edge cases as we can. This stressful responsibility is, I suppose, not obvious. so, if you’re n…
Eugene Vinitsky: Lots of new folks trying to write papers so it’s important to know: if there’s a mistake in the paper, the responsibility falls on you. You cannot offload it to the AI assistant.
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3 experts · 3 posts · 2d ago
Karl Bode Alejandra Caraballo Nafnlaus 🇮🇸 🇺🇦
Matches Opportunity & adoption
“$72 billion of this was a paper loss from convertible notes. It wasn't actual money spent. Only $8 billion of that was actually a real loss. The issue is that the loss will likely scale faster than…” evidence ↗
Karl Bode: Anthropic logged net loss of over $80 billion in first half of 2026, WSJ reports reut.rs/4z2Zi9J
Alejandra Caraballo: $72 billion of this was a paper loss from convertible notes. It wasn't actual money spent. Only $8 billion of that was actually a real loss. The issue is that the loss will likely scale faster than…
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